This invention relates to electronic scanning of images, and more particularly to the scanning of photographic prints by reflected light and the removal of surface defects.
The present invention is an improvement on a method of correcting defects in a film image using infrared light as taught in U.S. Pat. No. 5,266,805 issued to Albert Edgar, the present inventor. The underlying physics enabling this method is illustrated in FIG. 1. In FIG. 1 it is noted that with any color of visible light, such as green light, one or more dyes in a color film absorb light with corresponding low transmission of the light; however, in the infrared wavelength range, the common image forming dyes have a very high transmission approaching 100%, and therefore have little or no effect on transmitted infrared light. On the other hand, most surface defects, such as scratches, fingerprints, or dust particles, degrade the image by refracting light from the optical path. This refraction induced transmission loss is nearly the same in the infrared as it is in the visible, as illustrated in FIG. 1.
Continuing now with FIG. 2, a film substrate 201 has embedded in it a dye layer 202. Infrared light 204 (FIG. 2a) impinging on the film 201 will pass through the film and emerge as light 206 with nearly 100% transmission because the dye 202 does not absorb infrared light. Conversely, visible light 208 (FIG. 2b) will be absorbed by the dye 202. If the dye density is selected for a 25% transmission, then 25% of the visible light 210 will be transmitted by the film 201.
Now assume the film is scratched with a notch 214 (FIG. 2c) such that 20% of the light will be refracted from the optical path before penetrating into the film 201. When a beam of infrared light 216 strikes the film 201, 20% will be diverted due to the notch 214, and a beam of 80% of the infrared light 218 will be transmitted. Finally, let a beam of visible light 220 (FIG. 2d) impinge on the film 201. Again 20% of the light 222 is diverted by the notch 214, leaving 80% of the visible light to penetrate the film 201. However, the dye layer 202 absorbs 75% of that 80%, leaving only 25% of 80%, or 20% of the original light 224, to pass through the film 201.
In general, the beam left undiverted by the defect is further divided by dye absorption. In visible light, that absorption represents the desired image, but in infrared that dye absorption is virtually zero. Thus, by dividing the visible light actually transmitted for each pixel by the infrared light actually transmitted, the effect of the defect is divided out, just like division by a norming control experiment, and the defect is thereby corrected. This division process is further clarified in FIG. 3. The value of a pixel 302 of a visible light image 304 is divided with operator 306 by the value of the corresponding pixel 308 of the infrared light image 310. The resultant value is placed into pixel 312 of the corrected image 314. Typically, the process is repeated with visible image 304 received under blue light, then green light, then red light to generate three corrected images representing the blue, green, and red channels of the image 304.
FIG. 4 is similar to FIG. 3 in that it shows a process for removing the effect of defects from a visible light image 404 using an infrared light image 406. Although the operator 408 in FIG. 4 is a subtraction, FIG. 4 is mathematically identical to FIG. 3 because the same result is obtained either by dividing two numbers, or by taking the logarithm of each, subtracting the two values in the logarithmic space, then taking the inverse logarithm of the result. However, the arrangement of FIG. 4 enables many additional useful functions because within the dotted line 402, the signals from images 404 and 406 may be split and recombined with a variety of linear functions that would not be possible with the nonlinear processing using the division operator of FIG. 3.
For example, in FIG. 5 a visible image 502 and an infrared image 504 are processed by logarithmic function blocks 506 and 508, respectively, to enter the linear processing dotted block 510 equivalent to block 402 of FIG. 4. After processing within block 510 is completed, the antilog is taken at function block 512 to produce the corrected image 514.
Internal to linear processing block 510, the logarithmic versions of the visible and infrared images are divided into high pass and low pass images with function blocks 520, 522, 524, and 526. These function blocks are selected such that when the output of the high and low pass blocks are added, the original input results. Further, the high pass function blocks 522 and 526 are equal, and the low pass function blocks 520 and 524 are equal. Under these assumptions, and under the further temporary assumption that the gain block 530 is unity, the topology in linear block 510 produces a result identical to the single subtraction element 408 for FIG. 4.
Without the logarithmic function blocks 506, 508, and 512, the split frequency topology shown in block 510 would not work. The output of a high pass filter, such as blocks 522 and 526, averages zero because any sustained bias away from zero is a low frequency that is filtered out in a high frequency block. A signal that averages to zero in small regions obviously passes through zero within those small regions. If function block 540 were a division, as would be required without the logarithmic operators, then the high pass visible signal 542 would often be divided by the zero values as the high pass infrared signal 544 passed through zero, resulting in an infinite high pass corrected signal 546, which obviously would give erroneous results. However, as configured with block 540 as a subtraction, the process is seen to avoid this problem.
The split frequency topology of FIG. 5 appears to be a complicated way to produce a mathematically equal result to that produced by the simple topology of FIG. 3 and FIG. 4. However, by separating the high frequencies as shown in FIG. 5, it is possible to overcome limitations in the scanner system by now allowing the gain block 530 to vary from unity. A typical scanner will resolve less detail in infrared light than in visible light. By letting gain block 530 have a value greater than unity, this deficiency can be controlled and corrected.
Often, however, the smudging of detail by a scanner in the infrared region relative to the visible region will vary across the image with focus shifts or the nature of each defect. By allowing the gain block 530 to vary with each section of the image, a much better correction is obtained. In particular, the value of gain is selected such that after subtraction with function block 540, the resulting high frequency signal 546 is as uncorrelated to the high frequency defect signal 548 as possible. If given the task, a human operator would subtract more or less of the defect signal 548 as controlled by turning the xe2x80x9cknobxe2x80x9d of gain block 530. The human operator would stop when the defect xe2x80x9cdisappearsxe2x80x9d from corrected image signal 546 as seen by viewing the corrected image 514. This point is noted by the human operator as xe2x80x9cdisappearancexe2x80x9d of the defect and is mathematically defined as the point at which the defect signal 544 or 548 and the corrected signal 546 are uncorrelated. This process could be repeated for each segment of the image with slightly different values of gain resulting as the optimum gain for each segment.
Despite the flexibility introduced by the gain block 530 of FIG. 5, it has been found that often a defect is incompletely nulled because deficiencies in the scanner cause the defect to look different in the infrared and the visible, such that no setting of gain can eliminate all aspects of the defect.
A need has thus arisen for an improved method for image defect correction.
In accordance with the present invention, surface defects in a reflection scan of an image consisting of pixels made with visible light are corrected by using a scan of the image consisting of pixels made with infrared light. This correction of surface defects is performed by first establishing for each pixel an upper and lower bound for defect intensity based on the infrared record. The corresponding visible pixel is then corrected by substracting the combination of upper and lower bound resulting in a corrected pixel.